ProfineAI

ProfineAI / profine-cli

Public

Profine automatically profiles and optimizes PyTorch training jobs on real GPUs, delivering measurable speedups and lower GPU costs before teams waste days tuning configs by hand.

profine.ai ai-agents automated-optimization benchmark cli command-line-tool
10
0
100% credibility
Found May 14, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Profine is a command-line tool that profiles PyTorch training scripts on remote GPUs, diagnoses performance bottlenecks with AI analysis, suggests cataloged optimizations, automatically applies code edits, and benchmarks measured speedups while verifying correctness.

How It Works

1
📦 Get Profine

Download this free tool that helps speed up your AI training programs with one simple command.

2
🔗 Connect helpers

Link it to cloud computers for powerful testing and a smart assistant for advice—no tech setup needed.

3
🚀 Test your program

Point it at your training script and let it run tests on fast machines to see what's slowing things down.

4
💡 Spot slowdowns

Get a clear report showing exactly where time is wasted, like slow math steps or memory hogs.

5
✨ Try speedup ideas

Pick the top suggestions and let it safely update your code with proven fixes.

✅ See real gains

Run quick checks to confirm it's faster and still accurate—often 2-3x quicker training!

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AI-Generated Review

What is profine-cli?

Profine-cli is a Python CLI that automatically profiles PyTorch training jobs on real GPUs via Modal, diagnoses bottlenecks, suggests optimizations from a curated catalog, edits your code, and benchmarks speedups with loss correctness checks. It delivers measurable improvements—like 3x faster steps and 68% less memory on minGPT—before you waste days tuning configs by hand. Run `profine run-all train.py --hardware 1x_a100` for the full pipeline, outputting edited scripts and reports.

Why is it gaining traction?

Unlike manual profiling tools or vague LLM code gen, profine-cli runs everything on actual GPUs (T4 to H100 presets), stacks optimizations like BF16, torch.compile, and FlashAttention with verified benchmarks, and supports local LLMs for privacy. It cuts GPU costs by quantifying ROI upfront, with reproducible seeds and auto-healing for failed runs—devs love shipping proven wins without local hardware hassles.

Who should use this?

ML engineers fine-tuning LLMs or training transformers on cloud GPUs, especially teams iterating on PyTorch scripts like nanoGPT where attention or matmuls dominate time. Ideal for devs optimizing jobs on Modal who want lower costs and faster iterations without deep PyTorch internals knowledge—skip if you're already hand-tuning with torch.profiler.

Verdict

Try it for quick wins on standard PyTorch training; the pipeline shines on common bottlenecks. At 10 stars and 1.0% credibility, it's early—solid docs and PyPI packaging, but watch for edge cases in complex multi-file projects.

(198 words)

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